How does Korean Speech To Text work?
- Automatic Speech Recognition (ASR). ASR analyzes spoken language and converts it into text through software algorithms that recognize phonetic sounds and patterns.
- Neural Networks. Neural networks are used to improve the accuracy of speech recognition by learning from large datasets of spoken Korean language.
- Language Modeling. Language modeling uses statistical methods to predict the most likely sequence of words that matches the spoken input, enhancing transcription quality.
- Acoustic Modeling. Acoustic modeling uses sound data to understand how different phonemes of the Korean language correlate with written text, improving recognition accuracy.